Classification and Regression Algorithms for Brain Computer Interfacing

The Brain-Computer Interface (BCI) stands as a groundbreaking technology, establishing a direct communication channel linking the human brain and external devices, enabling seamless interaction and control. This project focuses on the development of a BCI system utilizing machine learning techniques, specifically classification and regression algorithms. The brain-computer interface (BCI) facilitates a connection between the brain and the external world by interpreting physiological information generated during cognitive activities. Recent progress in neuroscience and machine learning has catalyzed transformative developments in BCI technology. This research study explores the implementation of advanced algorithms, specifically focusing on classification and regression techniques to enhance the performance and accuracy of BCI systems.